Compare models
Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.
4 is the maximum. Remove one to add another.
| Attribute | S1s1 | DeepSeek V4.1 Flashdeepseek-v4.1-flash | Muse Spark 1.3muse-spark-1.3 | GPT-6 Lunagpt-6-luna |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0 / 1M | $0.30 / 1M | $1.25 / 1M | $0.10 / 1M |
| Output | $0 / 1M | $1.20 / 1M | $4.25 / 1M | $0.50 / 1M |
| Cache Write (5m) | Not applicable | $0.30 / 1M | $1.25 / 1M | $0.10 / 1M |
| Cache Write (1h) | Not applicable | $0.30 / 1M | $1.25 / 1M | $0.10 / 1M |
| Cache Read | Not applicable | $0.30 / 1M | $1.25 / 1M | $0.10 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | N/A | 1M | 1M | 1.1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | No | Yes | Yes | Yes |
| Function Calling | No | Yes | Yes | Yes |
| JSON Mode | No | Yes | Yes | Yes |
| Streaming | No | Yes | Yes | Yes |
| Catalogue | ||||
| Provider | Fish Audio | DeepSeek | Meta | OpenAI |
| Category | voice | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | 2026-07-29 | — | — | — |
| Description | ||||
| Summary | Fish Audio S1 text-to-speech. Billed per UTF-8 byte of input text. | DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion. | Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows. | GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability. |